| Literature DB >> 33925124 |
Eunjung Kim1,2, Sihyun Park1, Hyunjin Park1, Jangduck Choi1, Hae-Jung Yoon1, Jeong-Han Kim2.
Abstract
The objective of this study is to develop a comprehensive and simple method for the simultaneous determination of anthelmintic and antiprotozoal drug residues in fish. For sample preparation, we used the "quick, easy, cheap, effective, rugged, and safe" (QuEChERS) method with a simple modification. The sample was extracted with water and 1% formic acid in acetonitrile/methanol (MeCN/MeOH) (95:5, v/v), followed by phase separation (salting out) with MgSO4 and NaCl (4:1, w/w). After centrifugation, an aliquot of the extract was purified by dispersive solid-phase extraction (d-SPE) prior to liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. The method was validated at three concentration levels for all matrices, in accordance with the Codex guidelines (CAC/GL-71). Quantitative analysis was performed using the method of matrix-matched calibration. The recoveries were between 60.6% and 119.9%, with coefficients of variation (CV) <30% for all matrices. The limit of quantitation (LOQ) of the method ranged from 0.02 μg kg-1 to 4.8 μg kg-1 for all matrices. This comprehensive method can be used for the investigation of both anthelmintic and antiprotozoal drugs belonging to different chemical families in fishery products.Entities:
Keywords: LC-MS/MS; anthelmintics; antiprotozoals; fishery product; residues
Mesh:
Substances:
Year: 2021 PMID: 33925124 PMCID: PMC8125621 DOI: 10.3390/molecules26092575
Source DB: PubMed Journal: Molecules ISSN: 1420-3049 Impact factor: 4.411
Summary of method validation parameters; recovery and coefficient value (CV) for the 71 target veterinary drugs (n = 5).
| Recovery | Number of Veterinary Drugs (Percentage, %) | |||
|---|---|---|---|---|
| Flatfish | Eel | Shrimp | Manila Clam | |
|
| (CV 2.3%~28.4%) | (CV 2.8%~30.2%) | (CV 0.8%~26.6%) | (CV 1.7%~29.7%) |
| 60% to 80% | 3(4.2%) | 7(9.9%) | 11(15.5%) | 5(7.0%) |
| 80% to 100% | 38(53.5%) | 35(49.3%) | 35(49.3%) | 30(42.3%) |
| 100% to 120% | 30(42.3%) | 29(40.8%) | 25(35.2%) | 36(50.7%) |
|
| (CV 1.7%~23.1%) | (CV 1.5%~24.6%) | (CV 1.1%~14.2%) | (CV 2.2%~27.6%) |
| 60% to 80% | 1(1.4%) | 1(1.4%) | 0(0.0%) | 2(2.8%) |
| 80% to 100% | 24(33.8%) | 29(40.8%) | 38(53.5%) | 31(43.7%) |
| 100% to 120% | 46(64.8%) | 41(57.7%) | 33(46.5%) | 38(53.5%) |
|
| (CV 0.9%~18.8%) | (CV 1.5%~20.4%) | (CV 1.0%~17.5%) | (CV 1.8%~22.2%) |
| 60% to 80% | 1(1.4%) | 1(1.4%) | 0(0.0%) | 1(1.4%) |
| 80% to 100% | 33(46.5%) | 37(52.1%) | 44(62.0%) | 11(15.5%) |
| 100% to 120% | 37(52.1%) | 33(46.5%) | 27(38.0%) | 59(83.1%) |
Figure 1Distribution of the limit of quantitation.
Figure 2Distribution of matrix effects.